Prediction and model-assisted estimation of diameter distributions using Norwegian national forest inventory and airborne laser scanning data

作     者：Raty, Janne Astrup, Rasmus Breidenbach, Johannes 

作者机构：Norwegian Inst Bioecon Res NIBIO Div Forest & Forest Resources Natl Forest Inventory Hogskoleveien 8 N-1433 As Norway 

出 版 物：《CANADIAN JOURNAL OF FOREST RESEARCH》 (加拿大林业研究杂志)

年 卷 期：2021年第51卷第10期

页      面：1521-1533页

核心收录：

学科分类：0907[农学-林学] 08[工学] 0829[工学-林业工程] 09[农学] 

基　　金：NIBIO (Norwegian Institute of Bioeconomy Research) PRECISION project (NFR) 

主　　题：generalized linear models linear mixed-effects models most similar neighbor approach number of stems systematic sampling 

摘      要：Diameter at breast height (DBH) distributions offer valuable information for operational and strategic forest management decisions. We predicted DBH distributions using Norwegian national forest inventory and airborne laser scanning data and compared the predictive performances of linear mixed-effects (PPM), generalized linear-mixed (GLM), and k nearest-neighbor (NN) models. While GLM resulted in smaller prediction errors than PPM, both were clearly outperformed by NN. We therefore studied the ability of the NN model to improve the precision of stem frequency estimates by DBH classes in the 8.7 Mha study area using a model-assisted (MA) estimator suitable for systematic sampling. MA estimates yielded greater than or approximately equal efficiencies as direct estimates using field data only. The relative efficiencies (REs) associated with the MA estimates ranged between 0.95-1.47 and 0.96-1.67 for 2 and 6 cm DBH class widths, respectively, when dominant tree species were assumed to be known. The use of a predicted tree species map, instead of the observed information, decreased the REs by up to 10%.